Senior Machine Learning Engineer (GCP)

Tiger Analytics is looking for a skilled and innovative Machine Learning Engineer with handson experience in Google Cloud Platform (GCP) and Vertex AI to design, build, and deploy scalable ML solutions. You will play a key role in operationalizing machine learning models and driving the endtoend ML lifecycle, from data ingestion to model serving and monitoring.

Key Responsibilities:

• Develop, train, and optimize ML models using Vertex AI, including Vertex Pipelines, AutoML, and custom model training.
• Design and build scalable ML pipelines for feature engineering, training, evaluation, and deployment.
• Deploy models to production using Vertex AI endpoints and integrate with downstream applications or APIs.
• Collaborate with data scientists, data engineers, and MLOps teams to enable reproducible and reliable ML workflows.
• Monitor model performance and set up alerting, retraining triggers, and drift detection mechanisms.
• Utilize GCP services such as BigQuery, Dataflow, Cloud Functions, PubSub, and GCS in ML workflows.
• Apply CICD principles to ML models using Vertex AI Pipelines, Cloud Build, and GitOps practices.
• Implement model governance, versioning, explainability, and security best practices within Vertex AI.
• Document architecture decisions, workflows, and model lifecycle clearly for internal stakeholders.

• Requirements

  1. Advanced Generative AI
  Advanced RAG including Graph based hybrid retrieval
  Multimodal agent
  

  • Deep knowledge on ADK , Langchain Agentic Frameworks
  • Fine tuning and Distillation
    

  • 2. Python Expertise
    Expert in Python with strong OOP and functional programming skills
    Proficient in MLDL libraries: TensorFlow, PyTorch, scikitlearn, pandas, NumPy, PySpark
    Experience with productiongrade code, testing, and performance optimization
    
    3. GCP Cloud Architecture & Services
    Proficiency in GCP services such as:
    Vertex AI
    BigQuery
    Cloud Storage
    Cloud Run
    Cloud Functions
    PubSub
    Dataproc
    Dataflow
    Understanding of IAM, VPC
    
    6. API Development & Integration
    Designs and builds RESTful APIs using FastAPI or Flask
    Integrates ML models into APIs for realtime inference
    Implements authentication, logging, and performance optimization
    
    7. System Design & Scalability
    Designs endtoend AI systems with scalability and fault tolerance in mind
    Handson experience in developing distributed systems, microservices, and asynchronous processing

    Benefits

    This position offers an excellent opportunity for significant career development in a fastgrowing and challenging entrepreneurial environment with a high degree of individual responsibility.